The need for powerful analytics tools is not limited to any one industry or field, but there is an especially strong need for such tools to aid in analyzing chemical mixtures, including quantitatively identifying the relative distributions between the constituent chemical compounds that comprise such mixtures. Chromatography, and other such methods, provide rich detail, but such detail is only as useful as the capability of tools used to analyze it. Existing tools range from “eye-balling” chromatograms to merely observing the relative ratios of a few compounds among potentially hundreds of chemicals and compounds within a mixture. Further, the existing analytical chemistry techniques that analyze the relative abundance of a few well known major compounds fail to quantify the inter-relationship between the major as well as minor (e.g., rarely investigated) constituent compounds in a complex mixture.
For example, in petroleum mixtures or oil samples, hundreds of hydrocarbons are detected in a two-dimensional gas chromatography (GC×GC) dataset, but current approaches to “fingerprint” oil samples rely solely on comparing the relative abundances of molecular fossils (biomarkers) occurring within the oil sample. This approach is now decades old and may not be capable of working in the Gulf where researchers are currently faced with the BP spill problem of how to disentangle the BP oil in environmental samples from closely related natural oil seeps and other sources. This problem is not limited to the BP spill but extends to many other spills of distilled products and crudes. Further, additional problems remains. For example, the systems existing as they are today lack the ability to detect connectivity between wells based on oil sample fingerprinting.
Thus, in addition to the need for powerful high-resolution separation of compounds, there is a specific and clear need for analytical techniques and informational methods that can provide comprehensive interpretation for the rich intricate high-volume GC×GC data. Additionally, there is a specific and clear need to account quantitatively for the distinctions and similarities exhibited across all of the constituent compounds in a chemical mixture.